arXiv subjects

John Parejko

Publications and source records attributed to John Parejko.

12 recordsLinked to original sources

arXiv2021

Gaia EDR3 confirms that Westerlund 1 is closer and older than previously thought

Using {\it Gaia} Early Data Release 3 (EDR3) parallaxes and Bayesian inference, we infer a parallax of the Westerlund 1 (Wd1) cluster. We find a parallax of $0.34\pm{0.05}$ mas corresponding to a distance of $2.8^{+0.7}_{-0.6}$ kpc. The new {\it Gaia} EDR3 distance is consistent with our previous result using {\it Gaia} DR2 parallaxes. This confirms that Wd1 is less massive and older than previously assumed. Compared to DR2, the EDR3 individual parallax uncertainties for each star decreased by 30\%. However, the aggregate parallax uncertainty for the cluster remained the same. This suggests that the uncertainty is dominated by systematics, which is possibly due to crowding, motions within the cluster, or motions due to binary orbits.

astro-ph.GA↗

arXiv2020

Mitigation of LEO Satellite Brightness and Trail Effects on the Rubin Observatory LSST

We report studies on the mitigation of optical effects of bright low-Earth-orbit (LEO) satellites on Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST). These include options for pointing the telescope to avoid satellites, laboratory investigations of bright trails on the Rubin Observatory LSST camera sensors, algorithms for correcting image artifacts caused by bright trails, experiments on darkening SpaceX Starlink satellites, and ground-based follow-up observations. The original Starlink v0.9 satellites are g ~ 4.5 mag, and the initial experiment "DarkSat" is g ~ 6.1 mag. Future Starlink darkening plans may reach g ~ 7 mag, a brightness level that enables nonlinear image artifact correction to well below background noise. However, the satellite trails will still exist at a signal-to-noise ratio ~ 100, generating systematic errors that may impact data analysis and limit some science. For the Rubin Observatory 8.4-m mirror and a satellite at 550 km, the full width at half maximum of the trail is about 3" as the result of an out-of-focus effect, which helps avoid saturation by decreasing the peak surface brightness of the trail. For 48,000 LEOsats of apparent magnitude 4.5, about 1% of pixels in LSST nautical twilight images would need to be masked.

astro-ph.IM↗

arXiv2020

Inferring the parallax of Westerlund 1 from Gaia DR2

Westerlund 1 (Wd1) is potentially the largest star cluster in the Galaxy. That designation critically depends upon the distance to the cluster, yet the cluster is highly obscured, making luminosity-based distance estimates difficult. Using {\it Gaia} Data Release 2 (DR2) parallaxes and Bayesian inference, we infer a parallax of $0.35^{+0.07}_{-0.06}$ mas corresponding to a distance of $2.6^{+0.6}_{-0.4}$ kpc. To leverage the combined statistics of all stars in the direction of Wd1, we derive the Bayesian model for a cluster of stars hidden among Galactic field stars; this model includes the parallax zero-point. Previous estimates for the distance to Wd1 ranged from 1.0 to 5.5 kpc, although values around 5 kpc have usually been adopted. The {\it Gaia} DR2 parallaxes reduce the uncertainty from a factor of 3 to 18\% and rules out the most often quoted value of 5 kpc with 99\% confidence. This new distance allows for more accurate mass and age determinations for the stars in Wd1. For example, the previously inferred initial mass at the main-sequence turn-off was around 40 M$_{\odot}$; the new {\it Gaia} DR2 distance shifts this down to about 22 M$_{\odot}$. This has important implications for our understanding of the late stages of stellar evolution, including the initial mass of the magnetar and the LBV in Wd1. Similarly, the new distance suggests that the total cluster mass is about four times lower than previously calculated.

astro-ph.SR↗

arXiv2019

Machine Learning for the Zwicky Transient Facility

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

astro-ph.IM↗

arXiv2018

Low Metallicities and Old Ages for Three Ultra-Diffuse Galaxies in the Coma Cluster

A large population of ultra-diffuse galaxies (UDGs) was recently discovered in the Coma cluster. Here we present optical spectra of three such UDGs, DF7, DF44 and DF17, which have central surface brightnesses of $μ_g \approx 24.4-25.1$ mag arcsec$^{-2}$. The spectra were acquired as part of an ancillary program within the SDSS-IV MaNGA Survey. We stacked 19 fibers in the central regions from larger integral field units (IFUs) per source. With over 13.5 hours of on-source integration we achieved a mean signal-to-noise ratio (S/N) in the optical of $9.5$Å$^{-1}$, $7.9$Å$^{-1}$ and $5.0$Å$^{-1}$, respectively, for DF7, DF44 and DF17. Stellar population models applied to these spectra enable measurements of recession velocities, ages and metallicities. The recession velocities of DF7, DF44 and DF17 are $6599^{+40}_{-25}$km/s, $6402^{+41}_{-39}$km/s and $8315^{+43}_{-43}$km/s, spectroscopically confirming that all of them reside in the Coma cluster. The stellar populations of these three galaxies are old and metal-poor, with ages of $7.9^{+3.6}_{-2.5}$Gyr, $8.9^{+4.3}_{-3.3}$Gyr and $9.1^{+3.9}_{-5.5}$Gyr, and iron abundances of $\mathrm{[Fe/H]}$ $-1.0^{+0.3}_{-0.4}$, $-1.3^{+0.4}_{-0.4}$ and $-0.8^{+0.5}_{-0.5}$, respectively. Their stellar masses are $3$-$6\times10^8 M_\odot$. The UDGs in our sample are as old or older than galaxies at similar stellar mass or velocity dispersion (only DF44 has an independently measured dispersion). They all follow the well-established stellar mass$-$stellar metallicity relation, while DF44 lies below the velocity dispersion-metallicity relation. These results, combined with the fact that UDGs are unusually large for their stellar mass, suggest that stellar mass plays a more important role in setting stellar population properties for these galaxies than either size or surface brightness.

astro-ph.GA↗

arXiv2017

Forward Modeling of Large-Scale Structure: An open-source approach with Halotools

We present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. The package supports many of the common forms used to describe galaxy-halo models: the halo occupation distribution (HOD), the conditional luminosity function (CLF), abundance matching, and alternatives to these models that include effects such as environmental quenching or variable galaxy assembly bias. Satellite galaxies can be modeled to live in subhalos, or to follow custom number density profiles within their halos, including spatial and/or velocity bias with respect to the dark matter profile. The package has an optimized toolkit to make mock observations on a synthetic galaxy population, including galaxy clustering, galaxy-galaxy lensing, galaxy group identification, RSD multipoles, void statistics, pairwise velocities and others, allowing direct comparison to observations. Halotools is object-oriented, enabling complex models to be built from a set of simple, interchangeable components, including those of your own creation. Halotools has an automated testing suite and is exhaustively documented on http://halotools.readthedocs.io, which includes quickstart guides, source code notes and a large collection of tutorials. The documentation is effectively an online textbook on how to build and study empirical models of galaxy formation with Python.

astro-ph.IM↗

arXiv2016

The Astropy Problem

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed, written, and operated as a grassroots, self-organized, almost entirely volunteer effort while the software is used by the majority of the astronomical community. Despite this, the project has always been and remains to this day effectively unfunded. Further, contributors receive little or no formal recognition for creating and supporting what is now critical software. This paper explores the problem in detail, outlines possible solutions to correct this, and presents a few suggestions on how to address the sustainability of general purpose astronomical software.

astro-ph.IM↗

arXiv2015

SDSS-III Baryon Oscillation Spectroscopic Survey Data Release 12: galaxy target selection and large scale structure catalogues

The Baryon Oscillation Spectroscopic Survey (BOSS), part of the Sloan Digital Sky Survey (SDSS) III project, has provided the largest survey of galaxy redshifts available to date, in terms of both the number of galaxy redshifts measured by a single survey, and the effective cosmological volume covered. Key to analysing the clustering of these data to provide cosmological measurements is understanding the detailed properties of this sample. Potential issues include variations in the target catalogue caused by changes either in the targeting algorithm or properties of the data used, the pattern of spectroscopic observations, the spatial distribution of targets for which redshifts were not obtained, and variations in the target sky density due to observational systematics. We document here the target selection algorithms used to create the galaxy samples that comprise BOSS. We also present the algorithms used to create large scale structure catalogues for the final Data Release (DR12) samples and the associated random catalogues that quantify the survey mask. The algorithms are an evolution of those used by the BOSS team to construct catalogues from earlier data, and have been designed to accurately quantify the galaxy sample. The code used, designated MKSAMPLE, is released with this paper.

astro-ph.CO↗

arXiv2014

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations in the Data Release 10 and 11 galaxy samples

We present a one per cent measurement of the cosmic distance scale from the detections of the baryon acoustic oscillations in the clustering of galaxies from the Baryon Oscillation Spectroscopic Survey (BOSS), which is part of the Sloan Digital Sky Survey III (SDSS-III). Our results come from the Data Release 11 (DR11) sample, containing nearly one million galaxies and covering approximately $8\,500$ square degrees and the redshift range $0.2<z<0.7$. We also compare these results with those from the publicly released DR9 and DR10 samples. Assuming a concordance $Λ$CDM cosmological model, the DR11 sample covers a volume of 13\,Gpc${}^3$ and is the largest region of the Universe ever surveyed at this density. We measure the correlation function and power spectrum, including density-field reconstruction of the baryon acoustic oscillation (BAO) feature. The acoustic features are detected at a significance of over $7\,σ$ in both the correlation function and power spectrum. Fitting for the position of the acoustic features measures the distance relative to the sound horizon at the drag epoch, $r_d$, which has a value of $r_{d,{\rm fid}}=149.28\,$Mpc in our fiducial cosmology. We find $D_V=(1264\pm25\,{\rm Mpc})(r_d/r_{d,{\rm fid}})$ at $z=0.32$ and $D_V=(2056\pm20\,{\rm Mpc})(r_d/r_{d,{\rm fid}})$ at $z=0.57$. At 1.0 per cent, this latter measure is the most precise distance constraint ever obtained from a galaxy survey. Separating the clustering along and transverse to the line-of-sight yields measurements at $z=0.57$ of $D_A=(1421\pm20\,{\rm Mpc})(r_d/r_{d,{\rm fid}})$ and $H=(96.8\pm3.4\,{\rm km/s/Mpc})(r_{d,{\rm fid}}/r_d)$. Our measurements of the distance scale are in good agreement with previous BAO measurements and with the predictions from cosmic microwave background data for a spatially flat cold dark matter model with a cosmological constant.

astro-ph.CO↗

arXiv2012

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Analysis of potential systematics

We analyze the density field of galaxies observed by the Sloan Digital Sky Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) included in the SDSS Data Release Nine (DR9). DR9 includes spectroscopic redshifts for over 400,000 galaxies spread over a footprint of 3,275 deg^2. We identify, characterize, and mitigate the impact of sources of systematic uncertainty on large-scale clustering measurements, both for angular moments of the redshift-space correlation function and the spherically averaged power spectrum, P(k), in order to ensure that robust cosmological constraints will be obtained from these data. A correlation between the projected density of stars and the higher redshift (0.43 < z < 0.7) galaxy sample (the `CMASS' sample) due to imaging systematics imparts a systematic error that is larger than the statistical error of the clustering measurements at scales s > 120h^-1Mpc or k < 0.01hMpc^-1. We find that these errors can be ameliorated by weighting galaxies based on their surface brightness and the local stellar density. We use mock galaxy catalogs that simulate the CMASS selection function to determine that randomly selecting galaxy redshifts in order to simulate the radial selection function of a random sample imparts the least systematic error on correlation function measurements and that this systematic error is negligible for the spherically averaged correlation function. The methods we recommend for the calculation of clustering measurements using the CMASS sample are adopted in companion papers that locate the position of the baryon acoustic oscillation feature (Anderson et al. 2012), constrain cosmological models using the full shape of the correlation function (Sanchez et al. 2012), and measure the rate of structure growth (Reid et al. 2012). (abridged)

astro-ph.CO↗

arXiv2012

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations in the Data Release 9 Spectroscopic Galaxy Sample

We present measurements of galaxy clustering from the Baryon Oscillation Spectroscopic Survey (BOSS), which is part of the Sloan Digital Sky Survey III (SDSS-III). These use the Data Release 9 (DR9) CMASS sample, which contains 264,283 massive galaxies covering 3275 square degrees with an effective redshift z=0.57 and redshift range 0.43 < z < 0.7. Assuming a concordance Lambda-CDM cosmological model, this sample covers an effective volume of 2.2 Gpc^3, and represents the largest sample of the Universe ever surveyed at this density, n = 3 x 10^-4 h^-3 Mpc^3. We measure the angle-averaged galaxy correlation function and power spectrum, including density-field reconstruction of the baryon acoustic oscillation (BAO) feature. The acoustic features are detected at a significance of 5σin both the correlation function and power spectrum. Combining with the SDSS-II Luminous Red Galaxy Sample, the detection significance increases to 6.7σ. Fitting for the position of the acoustic features measures the distance to z=0.57 relative to the sound horizon DV /rs = 13.67 +/- 0.22 at z=0.57. Assuming a fiducial sound horizon of 153.19 Mpc, which matches cosmic microwave background constraints, this corresponds to a distance DV(z=0.57) = 2094 +/- 34 Mpc. At 1.7 per cent, this is the most precise distance constraint ever obtained from a galaxy survey. We place this result alongside previous BAO measurements in a cosmological distance ladder and find excellent agreement with the current supernova measurements. We use these distance measurements to constrain various cosmological models, finding continuing support for a flat Universe with a cosmological constant.

astro-ph.CO↗

arXiv2009

Galaxy Zoo Green Peas: Discovery of A Class of Compact Extremely Star-Forming Galaxies

We investigate a class of rapidly growing emission line galaxies, known as "Green Peas", first noted by volunteers in the Galaxy Zoo project because of their peculiar bright green colour and small size, unresolved in SDSS imaging. Their appearance is due to very strong optical emission lines, namely [O III] 5007 A, with an unusually large equivalent width of up to ~1000 A. We discuss a well-defined sample of 251 colour-selected objects, most of which are strongly star forming, although there are some AGN interlopers including 8 newly discovered narrow Line Seyfert 1 galaxies. The star-forming Peas are low mass galaxies (M~10^8.5 - 10^10 M_sun) with high star formation rates (~10 M_sun/yr), low metallicities (log[O/H] + 12 ~ 8.7) and low reddening (E(B-V) < 0.25) and they reside in low density environments. They have some of the highest specific star formation rates (up to ~10^{-8} yr^{-1}) seen in the local Universe, yielding doubling times for their stellar mass of hundreds of Myrs. The few star-forming Peas with HST imaging appear to have several clumps of bright star-forming regions and low surface density features that may indicate recent or ongoing mergers. The Peas are similar in size, mass, luminosity and metallicity to Luminous Blue Compact Galaxies. They are also similar to high redshift UV-luminous galaxies, e.g., Lyman-break galaxies and Lyman-alpha emitters, and therefore provide a local laboratory with which to study the extreme star formation processes that occur in high-redshift galaxies. Studying starbursting galaxies as a function of redshift is essential to understanding the build up of stellar mass in the Universe.

astro-ph.CO↗